Data Breakdown

Column

Chart A

ChartB <- reviews %>%
  filter (
    boro != 0
  ) %>%
  drop_na() %>%
  ggplot(aes(x = grade)) +
  geom_bar() +
  theme_classic() + 
  labs(
    title = "Restaraunts Mapped by Coordinates and Grade"
  ) + 
  facet_grid(~boro)

ggplotly(ChartB)

Column

Chart B

chartA <- reviews %>%
  filter (
    boro != 0
  ) %>%
  drop_na() %>%
   ggplot(aes(x = boro, y = score)) + 
     geom_violin(aes(fill = boro), color = "blue", alpha = .5) + 
     theme(legend.position = "bottom") + 
  labs(
    title = "Distribution of Scores by Boro (lower score is better)"
  )
  
ggplotly(chartA)

Chart C

ChartC <- reviews %>%
  filter (
    boro != 0,
    cuisine_description %in% c("American", "Pizza", "Mexican", "Chinese", "Pizza/Italian", "Korean", "Japanese")
  ) %>%
  drop_na() %>%
   ggplot(aes(x = cuisine_description)) + 
     geom_bar(color = "blue", alpha = .5) + 
     theme(legend.position = "bottom", axis.text.x = element_text(angle = 90)) + 
  labs(
    title = "Distribution of Scores by Boro (lower score is better)"
  ) +
  facet_grid(~boro)

ggplotly(ChartC)